SOTAVerified

Privacy Preserving

Papers

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Showing 1376–1400 of 2975 papers

TitleStatusHype
Temporal Gradient Inversion Attacks with Robust Optimization—0
AnoFel: Supporting Anonymity for Privacy-Preserving Federated Learning—0
Efficient Skip Connections Realization for Secure Inference on Encrypted Data—0
Personalized Graph Federated Learning with Differential Privacy—0
DP-HyPO: An Adaptive Private Hyperparameter Optimization Framework—0
Does Image Anonymization Impact Computer Vision Training?Code2
FheFL: Fully Homomorphic Encryption Friendly Privacy-Preserving Federated Learning with Byzantine Users—0
PriSampler: Mitigating Property Inference of Diffusion Models—0
Improving Fairness and Robustness in End-to-End Speech Recognition through unsupervised clustering—0
Event Encryption: Rethinking Privacy Exposure for Neuromorphic Imaging—0
Human-imperceptible, Machine-recognizable ImagesCode0
Towards Fairness in Personalized Ads Using Impression Variance Aware Reinforcement Learning—0
A Privacy-Preserving Federated Learning Approach for Kernel methods—0
Integrated Sensing, Computation, and Communication for UAV-assisted Federated Edge Learning—0
Jammer classification with Federated Learning—0
Over-the-Air Federated Learning In Broadband Communication—0
Privacy-Preserving by Design: Indoor Positioning System Using Wi-Fi Passive TDOA—0
Non-uniform Speaker Disentanglement For Depression Detection From Raw Speech SignalsCode1
A FAIR platform for reproducing mutational signature detection on tumor sequencing dataCode0
Quantifying Sample Anonymity in Score-Based Generative Models with Adversarial Fingerprinting—0
Privacy-Preserving Remote Heart Rate Estimation from Facial Videos—0
Federated Graph Learning for Low Probability of Detection in Wireless Ad-Hoc Networks—0
CRS-FL: Conditional Random Sampling for Communication-Efficient and Privacy-Preserving Federated Learning—0
Bytes Are All You Need: Transformers Operating Directly On File Bytes—0
Centralised rehearsal of decentralised cooperation: Multi-agent reinforcement learning for the scalable coordination of residential energy flexibility—0
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